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No-Code Artificial Intelligence

AI is transforming industries, but you don’t need to code to be part of the revolution. Join our no-code AI course to build real-world AI solutions faster.

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About This Course

In this No-Code AI Course, master no code AI tools like AWS SageMaker and Google AutoML to create machine learning models for sales forecasting, fraud detection, and even plant disease diagnosis.

Learn by doing…from predicting housing prices to analyzing healthcare data, you’ll tackle hands-on projects that solve actual business problems.

Skills You’ll Get

  • Build AI Models without Coding: Learn to create machine learning models using no-code tools like AWS SageMaker, DataRobot, and Google AutoML.
  • Solve Real-World Business Problems: Develop AI solutions for sales forecasting, fraud detection, healthcare analysis, and more.
  • Master No-Code AI Platforms: Get hands-on experience with top no-code AI tools for image recognition, NLP, and predictive analytics.
  • Deploy AI in Key Industries: Apply AI in finance, healthcare, cybersecurity, and marketing. No programming needed.
  • Optimize & Improve AI Models: Learn how to evaluate, refine, and enhance AI models for better accuracy and performance.
Download Course Outline

1

Preface

2

What is AI

  • Introduction to Artificial Intelligence
  • Types of AI systems
  • Introduction to Machine Learning
  • Supervised learning
  • Unsupervised learning
  • Reinforcement Learning
  • Bleeding edge AI research
  • Conclusion
  • Further readings
  • Questions
3

Getting Started with No-code AI

  • Introduction to no-code AI
  • History of no-code AI
  • Different types of no-code AI solutions
  • Advantages of no-code AI solutions
  • Conclusion
  • Questions
4

Building AI Model to Predict Housing Prices

  • Data selection
  • No-Code AI tool selection
  • Exploratory Data Analysis
  • Model selection
  • Training
  • Evaluation
  • Result and further improvements
  • Conclusion
5

Classifying Different Images

  • Data selection
  • No-Code AI tool selection
  • Data labeling
  • Training
  • Evaluation
  • Result and further improvements
  • Conclusion
  • Questions
6

Building AI Model to Perform Sales Forecasting

  • Data selection
  • No-code AI tool selection
  • Exploratory Data Analysis
  • Model selection
  • Training
  • Evaluation
  • Result and further improvements
  • Conclusion
7

Building AI Model to Find Fraudulent Claims

  • Data selection
  • No-Code AI tool selection
  • Exploratory Data Analysis
  • Model selection
  • Training
  • Evaluation
  • Result and further improvements
  • Conclusion
  • Questions
8

Building AI Model to Detect Diseases in Plants

  • Data selection
  • No-Code AI tool selection
  • Exploratory Data Analysis
  • Model selection
  • Training
  • Evaluation
  • Result and further improvements
  • Conclusion
  • Questions
9

Building AI Model to Create Targeted Customer Offerings

  • Data selection
  • No-Code AI tool selection
  • Exploratory Data Analysis
  • Model selection
  • Training
  • Evaluation
  • Result and Further improvements
  • Conclusion
  • Questions
10

Building AI Model for Healthcare Information Identification

  • Data selection
  • No-code AI tool selection
  • Exploratory Data Analysis
  • Model selection and training
  • Evaluation
  • Result and further improvements
  • Conclusion
  • Questions
11

Building AI Model for Video Action Recognition

  • Data selection
  • No-code AI tool selection
  • Exploratory Data Analysis
  • Model selection and training
  • Evaluation
  • Result and further improvements
  • Conclusion
  • Questions
12

Building AI Applications with Coded AI

  • Introduction to Python programming language
  • Popular AI libraries
  • Build AI projects with Python in Google Colab
  • Using pretrained models for AI Applications
  • Using Kaggle for AI and data science challenges
  • Conclusion
  • Questions

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No-code AI is rapidly growing, making AI accessible to non-technical professionals. Businesses will increasingly adopt no-code tools for faster, cost-effective AI solutions in marketing, healthcare, finance, and more. Expect more advanced automation, drag-and-drop AI model builders, and seamless integration with business workflows.

No, AI won’t replace programmers but will change their roles. AI (including no-code tools) automates repetitive coding tasks, allowing developers to focus on complex problem-solving, architecture, and innovation. Programmers who adapt by learning AI integration will remain in high demand.

Yes! No-code AI tools let you build, train, and deploy AI models without programming. Roles like AI business analysts, AI trainers, and automation specialists are emerging for non-coders. This AI course for non-technical individuals teaches you how to create real-world AI solutions—no coding required.

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